Interference management in multi-user wireless networks is a critical problem that needs to be addressed for enhancing network capacity. Cadambe and Jafar in V. Cadambe and S. Jafar, “Interference alignment and degrees of freedom of the-user interference channel,” Information Theory, IEEE Transactions on, vol. 54, no. 8, pp. 3425-3441, 2008, made an important advancement in this direction by proving that the sum capacity of a multi-user network is not fundamentally limited by the amount of interference. In contrast with the traditional view, the number of interference free signaling dimensions, referred to as Degrees of Freedom (DoF), were shown to scale linearly with the number of users. Subsequently, they proposed Interference Alignment (IA) based precoding to achieve linear scaling of DoF and sum capacity in the high signal-to-noise ratio (SNR) regime.
The key insight for IA is that perfect signal recovery is possible if interference does not span the entire received signal space (FIG. 1). As a result, a smaller subspace free of interference can be found where the desired signal can be projected while suppressing the interference to zero. Since the component of the desired signal lying in the interference space is lost after projection, the sum-rate scaling achieved comes at the expense of reduced SNR (see H. Sung, S. Park, K. Lee, and I. Lee, “Linear precoder designs for K-user interference channels,” Wireless Communications, IEEE Transactions on, vol. 9, no. 1, pp. 291-301, 2010). Therefore, in order to achieve optimal performance, the two spaces must be roughly orthogonal. However, as the results in O. El Ayach, S. Peters, and R. Heath, “The feasibility of interference alignment over measured MIMO-OFDM channels,” Vehicular Technology, IEEE Transactions on, vol. 59, no. 9, pp. 4309-4321, 2010, show, orthogonality (represented in terms of chordal distance) of the subspaces is influenced by the nature of the wireless channel and hence may not always be achievable in the real world. Further, the authors provided a feasibility study of IA over measured channels and established an empirical relation between sum-rate and distance between the signal and interference space. They quantified the effect of correlated channels on the sum capacity and showed the sub-optimality of IA at low SNR. Another experimental study reported in O. Gonzalez, D. Ramirez, I. Santamaria, J. Garcia-Naya, and L. Castedo, “Experimental validation of interference alignment techniques using a multiuser MIMO testbed,” in Smart Antennas (WSA), 2011 International ITG Workshop on. IEEE, 2011, pp. 1-8, showed similar degradation in the performance of IA because of practical effects such as collinearity of subspaces arising in real world channels.
On the other hand, reconfigurable antennas have been shown to enhance the performance of MIMO systems by increasing the channel capacity, diversity order and even have been shown to perform well in the low SNR regimes, J. Boerman and J. Bernhard, “Performance study of pattern reconfigurable antennas in MIMO communication systems,” Antennas and Propagation, IEEE Transactions on, vol. 56, no. 1, pp. 231-236, 2008; B. Cetiner, H. Jafarkhani, J. Qian, H. Yoo, A. Grau, and F. De Flaviis, “Multifunctional reconfigurable MEMS integrated antennas for adaptive MIMO systems,” Communications Magazine, IEEE, vol. 42, no. 12, pp. 62-70, 2004; and A. Sayeed and V. Raghavan, “Maximizing MIMO capacity in sparse multipath with reconfigurable antenna arrays,” Selected Topics in Signal Processing, IEEE Journal of, vol. 1, no. 1, pp. 156-166, 2007. The ability of reconfigurable antennas to dynamically alter the radiation patterns and provide multiple channel realizations enable MIMO systems to adapt according to physical link conditions which leads to improved capacity. In the context of IA, reconfigurable antennas have the potential to improve its sum-rate by providing potentially uncorrelated channel realizations.